A variety of modern Cyber-Physical Systems (CPSs) are distributed and asynchronous systems that are becoming the backbone for smart infrastructures and systems such as smart grids, power plants, medical appliances, social robots etc. The weaving of cyber components with the physical system improves resource utilization and system reliability. However, it makes the CPSs significantly vulnerable to several cyber threats by increasing the attack surfaces. In safety-critical cyber-physical systems, the primary focus is on safety assurance. Any mistake or ignorance in security analysis may greatly amplify the losses in the presence of cyber threats. Such security failure may result in severe damages that may range from affecting critical infrastructures up to even loss of human lives. Thus, an early-staged security modeling of these systems is a prominent issue and requires a systematic approach for modeling a secure design as well as performance evaluation of alternative designs for the same. An in-depth security analysis involves the identification of a standard set of evaluation metrics. The proposed work provides the design-time methodology to map and analyze system security qualitatively and quantitatively using Stochastic Petri nets and their fundamental properties. The effectiveness of the proposed methodology is evaluated using a Nuclear power plant (NPP) case study.

各种各样的现代网络物理系统（CPS）是分布式和异步系统，它们正成为智能基础架构和系统（如智能电网，发电厂，医疗设备，社交机器人等）的骨干。。网络组件与物理系统的编织提高了资源利用率和系统可靠性。但是，通过增加攻击面，它使CPS极易受到多种网络威胁的攻击。在对安全至关重要的网络物理系统中，主要重点是安全保证。安全分析中的任何错误或无知可能会在存在网络威胁的情况下大大放大损失。这种安全故障可能导致严重的损害，其损害范围可能从影响关键基础设施到人员伤亡。因此，这些系统的早期安全建模是一个突出的问题，并且需要一种系统的方法来对安全设计进行建模以及针对该替代设计的性能评估。深入的安全分析涉及确定一组标准的评估指标。拟议的工作提供了一种设计时方法，以利用随机Petri网及其基本属性来定性和定量地映射和分析系统安全性。使用核电厂（NPP）案例研究评估了所提出方法的有效性。